Calculating maximum morphine equivalent daily dose from prescription directions for use in the electronic health record: a case report

Author:

Goud Anil12,Kiefer Elizabeth1,Keller Michelle S234,Truong Lyna1,SooHoo Spencer12,Riggs Richard V12

Affiliation:

1. Enterprise Information Systems, Cedars-Sinai Medical Center, Los Angeles, California, USA

2. Division of Informatics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA

3. Division of General Internal Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA

4. Department of Health Policy and Management, UCLA Fielding School of Public Health, UCLA, Los Angeles, California, USA

Abstract

Abstract To demonstrate a process of calculating the maximum potential morphine milligram equivalent daily dose (MEDD) based on the prescription Sig for use in quality improvement initiatives. To calculate an opioid prescription’s maximum potential Sig-MEDD, we developed SQL code to determine a prescription’s maximum units/day using discrete field data and text-parsing in the prescription instructions. We validated the derived units/day calculation using 3000 Sigs, then compared the Sig-MEDD calculation against the Epic-MEDD calculator. Of the 101 782 outpatient opioid prescriptions ordered over 1 year, 80% used discrete-field Sigs, 7% used free-text Sigs, and 3% used both types. We determined units/day and calculated a Sig-MEDD for 98.3% of all the prescriptions, 99.99% of discrete-Sig prescriptions, and 81.5% of free-text-Sig prescriptions. Analyzing opioid prescription Sigs to determine a maximum potential Sig-MEDD provides greater insight into a patient’s risk for opioid exposure.

Funder

NIH

National Center for Advancing Translational Science

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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